3 citations · 3 across the 5 of their papers we have counts for
8 papers
Camera Bias in a Fine Grained Classification Task
Philip T. Jackson, Stephen Bonner, Ning Jia +3
We show that correlations between the camera used to acquire an image and the class label of that image can be exploited by convolutional neural networks (CNN), resulting in a mode…
Segmentation of Macular Edema Datasets with Small Residual 3D U-Net Architectures
Jonathan Frawley, Chris G. Willcocks, Maged Habib +3
This paper investigates the application of deep convolutional neural networks with prohibitively small datasets to the problem of macular edema segmentation. In particular, we inve…
Temporal Neighbourhood Aggregation: Predicting Future Links in Temporal Graphs via Recurrent Variational Graph Convolutions
Stephen Bonner, Amir Atapour-Abarghouei, Philip T Jackson +5
Graphs have become a crucial way to represent large, complex and often temporal datasets across a wide range of scientific disciplines. However, when graphs are used as input to ma…
TMIXT: A process flow for Transcribing MIXed handwritten and machine-printed Text
Fady Medhat, Mahnaz Mohammadi, Sardar Jaf +6
Handling large corpuses of documents is of significant importance in many fields, no more so than in the areas of crime investigation and defence, where an organisation may be pres…
Combining Mathematical Morphology and the Hilbert Transform for Fully Automatic Nuclei Detection in Fluorescence Microscopy
Carl J. Nelson, Philip T. G. Jackson, Boguslaw Obara
Accurate and reliable nuclei identification is an essential part of quantification in microscopy. A range of mathematical and machine learning approaches are used but all methods h…
Phenotypic Profiling of High Throughput Imaging Screens with Generic Deep Convolutional Features
Philip T. Jackson, Yinhai Wang, Sinead Knight +5
While deep learning has seen many recent applications to drug discovery, most have focused on predicting activity or toxicity directly from chemical structure. Phenotypic changes e…